Titlebook: Introducing HR Analytics with Machine Learning; Empowering Practitio Christopher M. Rosett,Austin Hagerty Book 2021 Springer Nature Switzer

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Book 2021itioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists

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Introductiond to get oriented to the realities of HR. This chapter concludes with a commitment to deliver content for both types of professionals in order to facilitate growth and provide value for all who are interested in getting started with HR Analytics and its more advanced applications.

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Machine Learning Project Managements, higher-than-normal ambiguity in ROI and business cases, and higher-than-normal post-implementation resource requirements. These and more are introduced to compare machine learning with more typical forms of HR project management.

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HR Analytics Ikigailearning into the mix and discusses how this implicit lean toward computer science and statistics may accidentally unbalance Ikigai. It is up to the practitioner to ensure balance is maintained so HR Analytics can be done well.

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Thinking About Your Problem-Solving Strategiesachine learning. Finally, this chapter considers that while machine learning stands to offer a lot to the world of applied analytics, it can also implicitly unbalance Analytics Ikigai so the prudent practitioner must take care to ensure this balance is maintained.